Regulation of metabolic arousal during insect dormancy

Many organisms, including mammalian hibernators and insects in diapause, are able to enter a dormant stage during which they dramatically suppress their metabolism to save energy. In addition, certain insects and mammals also demonstrate regular fluctuations between strong metabolic depression and bursts of higher metabolic activity known as periodic arousal. Chao Chen et al. used a combination of global metabolomics and isotope-based metabolic flux analysis in diapausing flesh fly pupae to elucidate the mechanisms regulating periodic arousal. They found that diapausing flesh fly pupae primarily relied on anaerobic glycolysis with tricarboxylic acid (TCA) cycle shutdown during metabolic depression, whereas they engaged in aerobic respiration through the TCA cycle during periodic arousal. These pupae also cleared anaerobic metabolites such as lactate and alanine and regenerated many depleted metabolites such as adenosine 5′-triphosphate and trehalose during arousal, similar to patterns observed in mammalian hibernators. Decreased reactive oxygen species (ROS) levels were found to induce metabolic arousal, and elevated ROS extended the duration of metabolic depression. ROS appeared to influence the timing of metabolic arousal by regulating the activity of the key metabolic enzymes pyruvate dehydrogenase and carnitine palmitoyltransferase I through the modulation of hypoxia inducible transcription factor. The researchers conclude that during flesh fly pupal diapause, ROS signaling regulates the switch to periodic arousal from metabolic depression and controls substrates entering the TCA cycle. — S.R.

PNAS e2017603118 (2021)

Elucidating how ice transitions to a ferroelectric state

Protons in ordinary bulk ice are typically disordered down to the lowest temperatures, but pure crystalline ice is thermodynamically expected to enter a ferroelectric (FE) state in which its protons occupy bond sites in a unique order. This proton-ordered FE phase is only achieved through metal hydroxide dopants such as KOH, and the mechanisms of this transition are not completely clear. In order to initially understand the FE ordering mechanisms of pure ice, J. Lasave et al. developed a bare-bones lattice model of ice that includes dipole–dipole interactions and only configurations which exactly satisfy the ice rule. They applied Monte Carlo strategies that allowed simulating large samples at low temperatures in this lattice model, and indeed they found, in full equilibrium, a first-order phase transition between proton-disordered, defect-free ice and low-temperature FE proton-ordered ice. Once inserted in the same model, dopants mimicking KOH were found to nucleate the transition by generating FE hydrogen-bond strings growing inside the proton-disordered bulk structures. The resulting kinetics qualitatively reproduce aspects of real KOH-doped ice, such as the dependence of the FE fraction on dopant concentration, quenching temperature, and the time evolution of the order parameter. The researchers conclude that their lattice model is able to shed light on the transition of ice into and out of its ferroelectric phase. — S.R.

PNAS e2018837118 (2020)

Sharpening clinical imaging with AI

The near-infrared (NIR)-IIb robes that produce the deepest tissue penetration and sharpest images with NIR imaging often have toxic elements, making them unfeasible for use in medical imaging for humans. FDA-approved biocompatible dyes, however, that typically detect fluorescence in the lower 700–1,000 nm range of the NIR spectrum, show comparatively poor image clarity and contrast. Zhuoran Ma et al. report that artificial neural networks can improve the signal-to-background ratio in NIR imaging, sharpening blurred images into high-resolution clinical pictures. Using approximately 2,800 in vivo images taken in mice, the authors trained, validated, and tested artificial neural networks with the intent to transform images produced in the shorter wavelengths into ones that resemble images taken in the NIR-IIb window of 1,500–1,700 nm. In a mouse injected with an FDA-approved dye, the neural network increased the signal-to-background ratio of lymph node images taken to greater than 100. The authors also compared the deep-learning enhanced imaging to actual NIR-IIb imaging of a mouse tumor. The enhanced image showed a 26.2 tumor-to-normal tissue signal ratio versus the actual image’s 30.8. According to the authors, deep-learning assisted imaging could improve diagnostics and image-guided surgery in the clinic. — T.H.D.

PNAS e2021446118 (2020)

Novel binding mechanisms substantiate synergistic activation of RXR–PXR

So-called endocrine disruptors—environmental pollutants that can cause reproductive, metabolic, or neurological disorders—target the pregnane X receptor (PXR), a nuclear receptor unique for its sensitivity to a wide range of compounds. Recent studies have demonstrated that PXR, in its heterodimeric form with the retinoid X receptor (RXR), can mediate both harmful and beneficial effects in response to xenobiotics, although the mechanisms by which pollutants activate PXR are still being investigated. Vanessa Delfosse, Tiphaine Huet, Deborah Harrus, Meritxell Granell, Maxime Bourguet, et al. utilize cell-based, biophysical, structural, and in vivo approaches to identify novel mixtures of chemicals, whose constituents have low individual affinity for PXR but combine synergistically to robustly activate the receptor. As an extension of their previous work, which showed that binary cocktails of xenobiotics synergistically activate RXR–PXR, the authors describe previously unreported binding mechanisms, substantiating the versatility of PXR’s ligand binding domain and the receptor’s role in sensing a diverse array of chemicals. Furthermore, the study shows that environmental compounds targeting RXR can boost the activity of two synergizing PXR ligands. The findings suggest that certain chemicals such as endocrine disruptors or pharmaceuticals, at levels deemed individually safe, can potentially interact synergistically and disrupt critical cell signaling. — T.J.

PNAS e2020551118 (2021)

Expanding the global map of antibiotic resistance

Antimicrobial resistance is a growing public health problem worldwide, and surveillance plays a key role in the development of mitigation strategies. But surveillance is expensive and therefore has been limited in low- and middle-income countries (LMIC), potentially further exacerbating antimicrobial resistance due to inappropriate antibiotic usage. To address this problem, Rik Oldenkamp et al. developed statistical models that use socioeconomic data to predict the prevalence of clinical antimicrobial resistance, thereby expanding the global map of antibiotic resistance. First, the authors modeled the association between existing antimicrobia resistance prevalence data for 74 countries and national socioeconomic profiles generated from 5,595 World Bank indicators. Next, the authors used the models to estimate the prevalence of antimicrobial resistance in countries lacking surveillance data. The models showed high predictive accuracy for six out of nine priority pathogens. Estimates for two priority pathogens—carbapenem resistant Acinetobacter baumannii and Escherichia coli resistant to third-generation cephalosporins—expanded coverage beyond the existing global prevalence map to include several billion additional people, mostly in LMIC, altogether representing 99% of the worldwide population. Moreover, the results suggest that the Middle East, Sub-Saharan Africa, and Pacific Islands should be prioritized for surveillance efforts. According to the authors, the study reveals a much-needed affordable method for systematically estimating the prevalence of antimicrobial resistance in LMIC and prioritizing surveillance efforts where resources are limited. — J.W.

PNAS e2013515118 (2020)

A cellular and genetic atlas of the lung offers insights into disease and development

Posted on December 18, 2020

Amy McDermott

Explorers need maps. That’s as true for hikers blazing trails as it is for molecular biologists striving to cure disease. A new atlas of the lungs, recently published in Nature, is the most comprehensive map ever of that vital organ. Continue Reading⇒